Methods for increasing the quality of computed tomography exposure series by way of image processing are generally known. Reference is made for instance to the publication DE 10 2005 038 940 A1, in which an edge-maintaining filter is used to improve the image. The publications P. Perona and J. Malik, “Scale space and edge detection using anistropic diffusion”, IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol. 12, pages 629-639, 1990, and J. Weickert, “Anisotropic Diffusion in Image Processing”, Teubner-Verlag, Stuttgart, Germany, 1998, disclose the use of diffusion filters in order to improve the image quality. Reference is also made to the publication DE 10 2005 012 654 A1, in which correlation calculations are used to filter image data in order also to improve the quality here. Each of the aforementioned publications are hereby incorporated herein by reference, in their entirety.
All these afore-cited known methods for improving the quality of image recordings by means of image processing nevertheless reach their limits if the relevant contrast is close to or even smaller than the noise. If CT perfusion examinations of the heart are examined, this indicates that the typical CT value changes, which are needed in order to identify the perfusion, lie in the range of approximately 2 to 20 HU, in other words 0.2 to 2% of the contrast between water and air. The image noise consequently plays a decisive role. To complicate matters further during the heart CT scan, the movement of the heart during the examination may result in motion blurs.